Mineral processing and extractive metallurgy


Kani Fan Avaran Shahvar company, having three dedicated laboratories and also possessing the mineral processing laboratory of Islamic Azad University, Shahrood branch, provides up-to-date services and knowledge base in the field of mineral processing and extractive metallurgy. What distinguishes this company from others is not only the ability to perform conventional and modern tests with sufficient accuracy in the company’s dedicated and contracted laboratories, but also the process of finding methods, designing test conditions and analyzing their results, which is in accordance with the knowledge and Up-to-date, modern and low-cost tools are designed and implemented for each project based on the results of mineral identification tests. Below is a brief description of these steps.

Methodology of tests:

Experts with up to date knowledge and experience,in this company in the mineral processing department, first select feasible or probable methods for mineral processing. This selection is done in the first stage based on the results of mineral identification and in the next stage by using detailed historiographical studies, similar industries, innovations, as well as new process and processing fields. After determining the possible processing methods, primary tests are performed to check the processability of the mineral samples according to the collected methods. The processing and process methods that are considered in the studies are not necessarily limited to traditional and common tools and include modern, creative methods and in many cases simpler and less costly than common methods. Also, if there is a need to perform special, modern or innovative tests, this company makes the equipment needed for the tests itself, and therefore, in many cases, this company uses equipment for the first time in the country that has been used less or not at all. For example, to investigate the response of the mineral material to Autogenous mill and semi-Autogenous mill, this company designed and built a pilot using the principles of design and modeling and generalizing the pilot to industrial and vice versa, and used in the laboratory of this company.

Design of experiments:

The design of experiments in this company is mainly done with the statistical design method of experiments. Design of Experiments or DOE is a statistical method and a powerful tool that, in the first step, identifies the variables of the process and then determines the best values of the variables to achieve the best results. Using the DOE tool, it is possible to change several process variables at the same time and determine through statistics which variable or combination of variables have the greatest impact on the result. Among the applications of the DOE method, we can mention the design and development of experiments and the improvement of the experiment design process.
Usually, performing any test is associated with spending money and time. Therefore, conducting experiments that have the least cost and time and provide the most information is the most ideal state. This cost and time increase exponentially when the number of variables increases. Therefore, there is a need for a method that can obtain more information about the process by spending less time and money. To explain more, suppose that the variables that affect the flotation performance of a copper sulfide mineral sample include granularity, the type of main and auxiliary collector, the consumption rate of the collector and auxiliary collector, the type of depressant and its concentration, the type of regulators and their concentrations, temperature, pH, The amount of aeration and many other variables. In the classic and usual methods to optimize a process, by keeping all the variables constant, the desired variable is changed within a certain range, and by observing its effect on the process response or copper recovery in the case of the recent example, the optimal value of the variable is selected. In this method, a very large number of experiments are required to reach the optimal conditions with high certainty. In the case of the last example, if there is a need to optimize at least 11 variables on copper recovery, if only 3 points are to be tested for each of the variables, the number of 3 to the power of 11 tests is required. While using the method of statistical design of experiments, the number of experiments can be significantly reduced without affecting the accuracy of the results. The method that best fulfills our goals at this company is the statistical design of the experiment, which is well executed by our technical team. In this method, all the variables affecting the results of the tests are changed based on a statistical model all at the same time, and after obtaining the results and statistical analysis and modeling, by performing the least number of tests, the most information from the system is obtained.

Conduct the experiment:

In the mineral processing and extractive metallurgy laboratory of Kani Fan Avaran Shahvar Company, there are various equipment and tools that are used in the projects. In addition, this company is ready to provide laboratory services to our customers. The mineral processing and extractive metallurgy laboratory services of this company are generally classified into three categories, which include the following:

  1. Mineral processing tests
  • Grinding tests
  • Milling tests
  • Ores concentration experiments using gravity, magnetic and flotation methods and other methods
  • Hydrometallurgical experiments
  • Leaching tests using different solvents on different samples
  • Solvent extraction tests
  • Process tests
  • Sedimentation tests
  • Filtration tests
Analysis of test results:

 When the design and analysis of the results of the experiments are done using statistical methods, after the calculations and statistical analyzes in the software, the optimal conditions for the variables will be obtained. However, the goal of analyzing the results of processing tests is not always to obtain optimal conditions for the influencing variables in the result of a test. One of these goals is to analyze the accuracy of experiments and the small value of human errors and random errors, which is done using methods based on artificial intelligence. Another goal of analyzing the results of processing and process tests is to extract the required parameters as process design criteria, when the process design is needed. Also, except in the analysis of hydrometallurgical tests, where elements are used as input parameters for recovery calculation, in processing tests, the numerical value of minerals and the calculation of mineral recovery are used. This work is done using the method of conversion of element to mineral. This work is important because, in fact, mineral processing methods, such as gravity, magnetic, or flotation methods, classify or concentrated minerals based on minerals and not elements. For example, in bauxite ore processing, the extraction of Diaspore mineral (economic aluminum mineral) and the removal of clay and aluminosilicate minerals are considered, the calculation of aluminum recovery cannot indicate the success or failure of the experiment because aluminum is present both in the main mineral and in waste minerals. In other words, if the test is not successful and no main mineral enters the concentrate and only waste minerals enter the concentrate, the recovery of aluminum will show a value that corresponds to the aluminum content of the waste minerals. Therefore, calculating recovery in mineral processing experiments based on mineral or phase recovery is a more reasonable measure to evaluate the success of an experiment. It should be noted that in this company, conversion of element to mineral and statistical design of experiments and analysis of their results are done using specialized software for each.